{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "718464bc-d3bc-4231-ae00-2a3bff2fab68",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import xgboost as xgb\n",
    "import seaborn as sns \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import numpy as np\n",
    "np.int = int\n",
    "import matplotlib.pyplot as plt\n",
    "#导入各种用于评估模型性能和参数优化的函数和类，例如均方误差（MSE）、均绝对误差（MAE）、决定系数（R2 Score）、解释方差分（explained variance score）等\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.metrics import mean_squared_error, r2_score,explained_variance_score,mean_absolute_percentage_error,mean_absolute_error\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "#导入XGBoost库中的XGBClassifier类，用于建立XGBoost分类模型，并导入plot_importance函数用于特征重要性可视化。\n",
    "from xgboost import XGBClassifier, plot_importance\n",
    "#导入互信息函数\n",
    "from sklearn.feature_selection import mutual_info_regression\n",
    "#导入lasso模型筛选特征变量\n",
    "from sklearn.linear_model import Lasso\n",
    "#导入Scikit-Optimize库中的贝叶斯优化相关的函数和类，用于超参数调优\n",
    "from skopt import gp_minimize\n",
    "from skopt.space import Real, Integer\n",
    "#导入交叉验证函数，用于评估模型性能\n",
    "from sklearn.model_selection import cross_val_score\n",
    "#导入随机森林回归模型\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "plt.rcParams['font.family'] = 'Times New Roman'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "50045870-09f1-4bd7-b236-4bafb6c90da6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#df = pd.read_excel('指标.xlsx')\n",
    "d = pd.read_excel(r'数据\\Feature.xlsx')\n",
    "dd = pd.read_excel(r'数据\\Features.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fc42cdc5-0483-4439-98af-3593081eff03",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "d=d.drop(columns=['Unnamed: 0'])\n",
    "dd=dd.drop(columns=['Unnamed: 0'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "59285029-518e-41c4-8d69-a0f2c2da0cba",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>AvgSurfT_inst_chengshu</th>\n",
       "      <th>LST_Day_1km_chousui</th>\n",
       "      <th>LST_Night_1km_fennie</th>\n",
       "      <th>soil_temperature_level_2_kaihua</th>\n",
       "      <th>soil_temperature_level_2_guanjiang</th>\n",
       "      <th>soil_temperature_level_2_shouhuo</th>\n",
       "      <th>soil_temperature_level_3_chousui</th>\n",
       "      <th>soil_temperature_level_3_kaihua</th>\n",
       "      <th>soil_temperature_level_3_guanjiang</th>\n",
       "      <th>...</th>\n",
       "      <th>SVAI_chousui</th>\n",
       "      <th>SVAI_kaihua</th>\n",
       "      <th>WDRVI_bajie</th>\n",
       "      <th>WDRVI_chousui</th>\n",
       "      <th>WDVI_bajie</th>\n",
       "      <th>WDVI_yunsui</th>\n",
       "      <th>WDVI_chousui</th>\n",
       "      <th>WDVI_kaihua</th>\n",
       "      <th>wet_kaihua</th>\n",
       "      <th>亩产</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>410522</td>\n",
       "      <td>301.830072</td>\n",
       "      <td>14770.448120</td>\n",
       "      <td>13653.260039</td>\n",
       "      <td>291.679432</td>\n",
       "      <td>294.485981</td>\n",
       "      <td>301.239969</td>\n",
       "      <td>287.263466</td>\n",
       "      <td>288.780851</td>\n",
       "      <td>290.517675</td>\n",
       "      <td>...</td>\n",
       "      <td>0.509428</td>\n",
       "      <td>0.502203</td>\n",
       "      <td>-0.270294</td>\n",
       "      <td>0.038094</td>\n",
       "      <td>0.312649</td>\n",
       "      <td>0.346212</td>\n",
       "      <td>0.380784</td>\n",
       "      <td>0.355850</td>\n",
       "      <td>-0.090609</td>\n",
       "      <td>7467.000138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>410421</td>\n",
       "      <td>301.881276</td>\n",
       "      <td>14811.998245</td>\n",
       "      <td>13724.830174</td>\n",
       "      <td>291.624652</td>\n",
       "      <td>294.462918</td>\n",
       "      <td>301.229017</td>\n",
       "      <td>287.616328</td>\n",
       "      <td>289.032764</td>\n",
       "      <td>290.784441</td>\n",
       "      <td>...</td>\n",
       "      <td>0.456349</td>\n",
       "      <td>0.444113</td>\n",
       "      <td>-0.220879</td>\n",
       "      <td>0.020097</td>\n",
       "      <td>0.272293</td>\n",
       "      <td>0.321097</td>\n",
       "      <td>0.313054</td>\n",
       "      <td>0.308834</td>\n",
       "      <td>-0.088144</td>\n",
       "      <td>5972.666001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>411726</td>\n",
       "      <td>298.990822</td>\n",
       "      <td>15035.873561</td>\n",
       "      <td>13760.252546</td>\n",
       "      <td>291.141219</td>\n",
       "      <td>293.187955</td>\n",
       "      <td>298.777454</td>\n",
       "      <td>287.204259</td>\n",
       "      <td>288.763693</td>\n",
       "      <td>290.271875</td>\n",
       "      <td>...</td>\n",
       "      <td>0.375751</td>\n",
       "      <td>0.406768</td>\n",
       "      <td>-0.273682</td>\n",
       "      <td>-0.176015</td>\n",
       "      <td>0.255247</td>\n",
       "      <td>0.291260</td>\n",
       "      <td>0.276982</td>\n",
       "      <td>0.277341</td>\n",
       "      <td>-0.107184</td>\n",
       "      <td>5687.791498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>410822</td>\n",
       "      <td>302.326105</td>\n",
       "      <td>14909.855104</td>\n",
       "      <td>13684.031442</td>\n",
       "      <td>291.393057</td>\n",
       "      <td>294.128413</td>\n",
       "      <td>300.920627</td>\n",
       "      <td>286.732262</td>\n",
       "      <td>288.209019</td>\n",
       "      <td>290.136585</td>\n",
       "      <td>...</td>\n",
       "      <td>0.466787</td>\n",
       "      <td>0.392344</td>\n",
       "      <td>-0.305916</td>\n",
       "      <td>0.009030</td>\n",
       "      <td>0.277992</td>\n",
       "      <td>0.313744</td>\n",
       "      <td>0.335973</td>\n",
       "      <td>0.327689</td>\n",
       "      <td>-0.062063</td>\n",
       "      <td>7959.597222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>411082</td>\n",
       "      <td>302.665974</td>\n",
       "      <td>14764.439462</td>\n",
       "      <td>13685.820730</td>\n",
       "      <td>292.812644</td>\n",
       "      <td>295.863324</td>\n",
       "      <td>302.456445</td>\n",
       "      <td>288.378758</td>\n",
       "      <td>289.948855</td>\n",
       "      <td>291.813767</td>\n",
       "      <td>...</td>\n",
       "      <td>0.479437</td>\n",
       "      <td>0.456340</td>\n",
       "      <td>-0.155182</td>\n",
       "      <td>0.027083</td>\n",
       "      <td>0.329961</td>\n",
       "      <td>0.356682</td>\n",
       "      <td>0.342203</td>\n",
       "      <td>0.353976</td>\n",
       "      <td>-0.074036</td>\n",
       "      <td>7662.496889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>411081</td>\n",
       "      <td>302.379726</td>\n",
       "      <td>14864.959928</td>\n",
       "      <td>13716.550674</td>\n",
       "      <td>292.036420</td>\n",
       "      <td>294.927847</td>\n",
       "      <td>301.419777</td>\n",
       "      <td>287.740673</td>\n",
       "      <td>289.256381</td>\n",
       "      <td>291.034992</td>\n",
       "      <td>...</td>\n",
       "      <td>0.438036</td>\n",
       "      <td>0.427608</td>\n",
       "      <td>-0.222630</td>\n",
       "      <td>-0.033628</td>\n",
       "      <td>0.276777</td>\n",
       "      <td>0.307460</td>\n",
       "      <td>0.306785</td>\n",
       "      <td>0.308283</td>\n",
       "      <td>-0.090942</td>\n",
       "      <td>6613.422500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>411424</td>\n",
       "      <td>302.404313</td>\n",
       "      <td>14767.178119</td>\n",
       "      <td>13698.554350</td>\n",
       "      <td>293.142870</td>\n",
       "      <td>296.125191</td>\n",
       "      <td>302.061064</td>\n",
       "      <td>288.739608</td>\n",
       "      <td>290.273988</td>\n",
       "      <td>292.107970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.537977</td>\n",
       "      <td>0.518776</td>\n",
       "      <td>-0.049587</td>\n",
       "      <td>0.143995</td>\n",
       "      <td>0.356591</td>\n",
       "      <td>0.372768</td>\n",
       "      <td>0.380640</td>\n",
       "      <td>0.392420</td>\n",
       "      <td>-0.074186</td>\n",
       "      <td>7579.469809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>411724</td>\n",
       "      <td>300.297286</td>\n",
       "      <td>14800.494981</td>\n",
       "      <td>13753.180467</td>\n",
       "      <td>291.750152</td>\n",
       "      <td>293.718662</td>\n",
       "      <td>299.219180</td>\n",
       "      <td>287.779530</td>\n",
       "      <td>289.413163</td>\n",
       "      <td>290.932713</td>\n",
       "      <td>...</td>\n",
       "      <td>0.511967</td>\n",
       "      <td>0.563379</td>\n",
       "      <td>0.082507</td>\n",
       "      <td>0.149694</td>\n",
       "      <td>0.389395</td>\n",
       "      <td>0.347135</td>\n",
       "      <td>0.345173</td>\n",
       "      <td>0.381115</td>\n",
       "      <td>-0.079914</td>\n",
       "      <td>5754.140236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>411324</td>\n",
       "      <td>300.250438</td>\n",
       "      <td>14870.302144</td>\n",
       "      <td>13755.946153</td>\n",
       "      <td>291.086794</td>\n",
       "      <td>293.369445</td>\n",
       "      <td>300.014684</td>\n",
       "      <td>287.141116</td>\n",
       "      <td>288.584741</td>\n",
       "      <td>290.356689</td>\n",
       "      <td>...</td>\n",
       "      <td>0.480808</td>\n",
       "      <td>0.460888</td>\n",
       "      <td>-0.102704</td>\n",
       "      <td>0.005744</td>\n",
       "      <td>0.309025</td>\n",
       "      <td>0.317261</td>\n",
       "      <td>0.348503</td>\n",
       "      <td>0.307512</td>\n",
       "      <td>-0.097445</td>\n",
       "      <td>5467.128359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>410122</td>\n",
       "      <td>302.101448</td>\n",
       "      <td>14900.316284</td>\n",
       "      <td>13728.293344</td>\n",
       "      <td>292.494994</td>\n",
       "      <td>295.405081</td>\n",
       "      <td>301.660649</td>\n",
       "      <td>288.002027</td>\n",
       "      <td>289.590761</td>\n",
       "      <td>291.427115</td>\n",
       "      <td>...</td>\n",
       "      <td>0.380461</td>\n",
       "      <td>0.390789</td>\n",
       "      <td>-0.356993</td>\n",
       "      <td>-0.172850</td>\n",
       "      <td>0.260427</td>\n",
       "      <td>0.290878</td>\n",
       "      <td>0.283795</td>\n",
       "      <td>0.284526</td>\n",
       "      <td>-0.095178</td>\n",
       "      <td>6637.200003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>102 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       NAME  AvgSurfT_inst_chengshu  LST_Day_1km_chousui   \n",
       "0    410522              301.830072         14770.448120  \\\n",
       "1    410421              301.881276         14811.998245   \n",
       "2    411726              298.990822         15035.873561   \n",
       "3    410822              302.326105         14909.855104   \n",
       "4    411082              302.665974         14764.439462   \n",
       "..      ...                     ...                  ...   \n",
       "97   411081              302.379726         14864.959928   \n",
       "98   411424              302.404313         14767.178119   \n",
       "99   411724              300.297286         14800.494981   \n",
       "100  411324              300.250438         14870.302144   \n",
       "101  410122              302.101448         14900.316284   \n",
       "\n",
       "     LST_Night_1km_fennie  soil_temperature_level_2_kaihua   \n",
       "0            13653.260039                       291.679432  \\\n",
       "1            13724.830174                       291.624652   \n",
       "2            13760.252546                       291.141219   \n",
       "3            13684.031442                       291.393057   \n",
       "4            13685.820730                       292.812644   \n",
       "..                    ...                              ...   \n",
       "97           13716.550674                       292.036420   \n",
       "98           13698.554350                       293.142870   \n",
       "99           13753.180467                       291.750152   \n",
       "100          13755.946153                       291.086794   \n",
       "101          13728.293344                       292.494994   \n",
       "\n",
       "     soil_temperature_level_2_guanjiang  soil_temperature_level_2_shouhuo   \n",
       "0                            294.485981                        301.239969  \\\n",
       "1                            294.462918                        301.229017   \n",
       "2                            293.187955                        298.777454   \n",
       "3                            294.128413                        300.920627   \n",
       "4                            295.863324                        302.456445   \n",
       "..                                  ...                               ...   \n",
       "97                           294.927847                        301.419777   \n",
       "98                           296.125191                        302.061064   \n",
       "99                           293.718662                        299.219180   \n",
       "100                          293.369445                        300.014684   \n",
       "101                          295.405081                        301.660649   \n",
       "\n",
       "     soil_temperature_level_3_chousui  soil_temperature_level_3_kaihua   \n",
       "0                          287.263466                       288.780851  \\\n",
       "1                          287.616328                       289.032764   \n",
       "2                          287.204259                       288.763693   \n",
       "3                          286.732262                       288.209019   \n",
       "4                          288.378758                       289.948855   \n",
       "..                                ...                              ...   \n",
       "97                         287.740673                       289.256381   \n",
       "98                         288.739608                       290.273988   \n",
       "99                         287.779530                       289.413163   \n",
       "100                        287.141116                       288.584741   \n",
       "101                        288.002027                       289.590761   \n",
       "\n",
       "     soil_temperature_level_3_guanjiang  ...  SVAI_chousui  SVAI_kaihua   \n",
       "0                            290.517675  ...      0.509428     0.502203  \\\n",
       "1                            290.784441  ...      0.456349     0.444113   \n",
       "2                            290.271875  ...      0.375751     0.406768   \n",
       "3                            290.136585  ...      0.466787     0.392344   \n",
       "4                            291.813767  ...      0.479437     0.456340   \n",
       "..                                  ...  ...           ...          ...   \n",
       "97                           291.034992  ...      0.438036     0.427608   \n",
       "98                           292.107970  ...      0.537977     0.518776   \n",
       "99                           290.932713  ...      0.511967     0.563379   \n",
       "100                          290.356689  ...      0.480808     0.460888   \n",
       "101                          291.427115  ...      0.380461     0.390789   \n",
       "\n",
       "     WDRVI_bajie  WDRVI_chousui  WDVI_bajie  WDVI_yunsui  WDVI_chousui   \n",
       "0      -0.270294       0.038094    0.312649     0.346212      0.380784  \\\n",
       "1      -0.220879       0.020097    0.272293     0.321097      0.313054   \n",
       "2      -0.273682      -0.176015    0.255247     0.291260      0.276982   \n",
       "3      -0.305916       0.009030    0.277992     0.313744      0.335973   \n",
       "4      -0.155182       0.027083    0.329961     0.356682      0.342203   \n",
       "..           ...            ...         ...          ...           ...   \n",
       "97     -0.222630      -0.033628    0.276777     0.307460      0.306785   \n",
       "98     -0.049587       0.143995    0.356591     0.372768      0.380640   \n",
       "99      0.082507       0.149694    0.389395     0.347135      0.345173   \n",
       "100    -0.102704       0.005744    0.309025     0.317261      0.348503   \n",
       "101    -0.356993      -0.172850    0.260427     0.290878      0.283795   \n",
       "\n",
       "     WDVI_kaihua  wet_kaihua           亩产  \n",
       "0       0.355850   -0.090609  7467.000138  \n",
       "1       0.308834   -0.088144  5972.666001  \n",
       "2       0.277341   -0.107184  5687.791498  \n",
       "3       0.327689   -0.062063  7959.597222  \n",
       "4       0.353976   -0.074036  7662.496889  \n",
       "..           ...         ...          ...  \n",
       "97      0.308283   -0.090942  6613.422500  \n",
       "98      0.392420   -0.074186  7579.469809  \n",
       "99      0.381115   -0.079914  5754.140236  \n",
       "100     0.307512   -0.097445  5467.128359  \n",
       "101     0.284526   -0.095178  6637.200003  \n",
       "\n",
       "[102 rows x 66 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75eb75d7-b0ce-4b35-98b5-91a2ab2470aa",
   "metadata": {
    "toc-hr-collapsed": true
   },
   "source": [
    "### 数据处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bb20839c-6340-44b1-a9e7-3c0c367273c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "删除特征的个数： 0\n",
      "出错特征的个数： 0\n",
      "删除的特征： []\n"
     ]
    }
   ],
   "source": [
    "#############删除缺失率高于05的特征\n",
    "null_list = []\n",
    "error_list = []\n",
    "for col in d.columns:\n",
    "    try:\n",
    "        null_list.append([col,d[col].isnull().sum() / d.shape[0]])\n",
    "    except:\n",
    "        error_list.append(col)\n",
    "null_df = pd.DataFrame(null_list,columns = ['特征名称','缺失率'])\n",
    "del_cols = null_df['特征名称'][null_df['缺失率'] >= 0.5]\n",
    "print('删除特征的个数：',len(del_cols))\n",
    "print('出错特征的个数：',len(error_list))\n",
    "print('删除的特征：',del_cols.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "aba9ae28-97f8-4fec-bc66-dd5fbfd318ec",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "删除特征的个数： 0\n",
      "出错特征的个数： 0\n",
      "删除的特征： []\n"
     ]
    }
   ],
   "source": [
    "#############表格中用绿色标记表示删除同值比例高的特征\n",
    "tz_list = []\n",
    "error_list = []\n",
    "for col in d.columns:\n",
    "    try:\n",
    "        tz_list.append([col,d[d[col] == d[col].mode()[0]].shape[0] / (d.shape[0] - d[col].isnull().sum())])\n",
    "    except:\n",
    "        error_list.append(col)\n",
    "tz_df = pd.DataFrame(tz_list,columns = ['特征名称','同值比例'])\n",
    "del_cols = tz_df['特征名称'][tz_df['同值比例'] >= 0.9]\n",
    "print('删除特征的个数：',len(del_cols))\n",
    "print('出错特征的个数：',len(error_list))\n",
    "print('删除的特征：',del_cols.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4032c90c-2e9f-47ff-9b43-383d7419a1d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "d=d.drop(columns=['GNDVI_kaihua','NDVI_chousui','OSAVI_chousui',\n",
    "                   'SVAI_chousui','SR_chousui'])\n",
    "dd=dd.drop(columns=['GNDVI_kaihua','NDVI_chousui','OSAVI_chousui',\n",
    "                   'SVAI_chousui','SR_chousui'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "40f2b7b5-6673-4d2b-a801-4118f2256435",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>AvgSurfT_inst_chengshu</th>\n",
       "      <th>LST_Day_1km_chousui</th>\n",
       "      <th>LST_Night_1km_fennie</th>\n",
       "      <th>soil_temperature_level_2_kaihua</th>\n",
       "      <th>soil_temperature_level_2_guanjiang</th>\n",
       "      <th>soil_temperature_level_2_shouhuo</th>\n",
       "      <th>soil_temperature_level_3_chousui</th>\n",
       "      <th>soil_temperature_level_3_kaihua</th>\n",
       "      <th>soil_temperature_level_3_guanjiang</th>\n",
       "      <th>...</th>\n",
       "      <th>SVAI_yunsui</th>\n",
       "      <th>SVAI_kaihua</th>\n",
       "      <th>WDRVI_bajie</th>\n",
       "      <th>WDRVI_chousui</th>\n",
       "      <th>WDVI_bajie</th>\n",
       "      <th>WDVI_yunsui</th>\n",
       "      <th>WDVI_chousui</th>\n",
       "      <th>WDVI_kaihua</th>\n",
       "      <th>wet_kaihua</th>\n",
       "      <th>亩产</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>410522</td>\n",
       "      <td>300.526136</td>\n",
       "      <td>14799.390577</td>\n",
       "      <td>13645.564675</td>\n",
       "      <td>290.520730</td>\n",
       "      <td>296.243766</td>\n",
       "      <td>301.744997</td>\n",
       "      <td>287.739688</td>\n",
       "      <td>288.165064</td>\n",
       "      <td>291.989798</td>\n",
       "      <td>...</td>\n",
       "      <td>0.516056</td>\n",
       "      <td>0.454165</td>\n",
       "      <td>-0.169349</td>\n",
       "      <td>0.059633</td>\n",
       "      <td>0.271899</td>\n",
       "      <td>0.369314</td>\n",
       "      <td>0.377903</td>\n",
       "      <td>0.332052</td>\n",
       "      <td>-0.085087</td>\n",
       "      <td>7421.059765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>410421</td>\n",
       "      <td>299.835257</td>\n",
       "      <td>14885.097859</td>\n",
       "      <td>13730.892892</td>\n",
       "      <td>289.450286</td>\n",
       "      <td>295.121816</td>\n",
       "      <td>301.575876</td>\n",
       "      <td>287.200556</td>\n",
       "      <td>287.550367</td>\n",
       "      <td>291.430691</td>\n",
       "      <td>...</td>\n",
       "      <td>0.503922</td>\n",
       "      <td>0.415995</td>\n",
       "      <td>-0.226778</td>\n",
       "      <td>0.047456</td>\n",
       "      <td>0.313414</td>\n",
       "      <td>0.345419</td>\n",
       "      <td>0.333503</td>\n",
       "      <td>0.303379</td>\n",
       "      <td>-0.090472</td>\n",
       "      <td>5905.753158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>411726</td>\n",
       "      <td>297.580502</td>\n",
       "      <td>14859.105485</td>\n",
       "      <td>13781.911220</td>\n",
       "      <td>288.378218</td>\n",
       "      <td>293.032866</td>\n",
       "      <td>298.607515</td>\n",
       "      <td>286.204292</td>\n",
       "      <td>286.648051</td>\n",
       "      <td>290.173229</td>\n",
       "      <td>...</td>\n",
       "      <td>0.457841</td>\n",
       "      <td>0.388374</td>\n",
       "      <td>-0.207561</td>\n",
       "      <td>-0.107692</td>\n",
       "      <td>0.246060</td>\n",
       "      <td>0.326980</td>\n",
       "      <td>0.303260</td>\n",
       "      <td>0.274792</td>\n",
       "      <td>-0.110333</td>\n",
       "      <td>5681.763483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>410822</td>\n",
       "      <td>301.204888</td>\n",
       "      <td>14937.506019</td>\n",
       "      <td>13697.783412</td>\n",
       "      <td>290.480633</td>\n",
       "      <td>296.267731</td>\n",
       "      <td>302.175285</td>\n",
       "      <td>287.549117</td>\n",
       "      <td>288.053063</td>\n",
       "      <td>291.999239</td>\n",
       "      <td>...</td>\n",
       "      <td>0.460758</td>\n",
       "      <td>0.391151</td>\n",
       "      <td>-0.225149</td>\n",
       "      <td>0.006908</td>\n",
       "      <td>0.295417</td>\n",
       "      <td>0.331463</td>\n",
       "      <td>0.379692</td>\n",
       "      <td>0.314127</td>\n",
       "      <td>-0.082004</td>\n",
       "      <td>7947.794351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>411082</td>\n",
       "      <td>301.276045</td>\n",
       "      <td>14916.375598</td>\n",
       "      <td>13670.887570</td>\n",
       "      <td>290.072776</td>\n",
       "      <td>295.931929</td>\n",
       "      <td>302.736960</td>\n",
       "      <td>287.686706</td>\n",
       "      <td>288.086720</td>\n",
       "      <td>292.011540</td>\n",
       "      <td>...</td>\n",
       "      <td>0.498366</td>\n",
       "      <td>0.463834</td>\n",
       "      <td>-0.114041</td>\n",
       "      <td>0.054913</td>\n",
       "      <td>0.330209</td>\n",
       "      <td>0.362398</td>\n",
       "      <td>0.363948</td>\n",
       "      <td>0.328066</td>\n",
       "      <td>-0.095346</td>\n",
       "      <td>7840.499426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>411081</td>\n",
       "      <td>299.835151</td>\n",
       "      <td>14885.009553</td>\n",
       "      <td>13761.025977</td>\n",
       "      <td>292.395091</td>\n",
       "      <td>296.486793</td>\n",
       "      <td>297.041116</td>\n",
       "      <td>287.623432</td>\n",
       "      <td>289.041457</td>\n",
       "      <td>292.435764</td>\n",
       "      <td>...</td>\n",
       "      <td>0.433611</td>\n",
       "      <td>0.419890</td>\n",
       "      <td>-0.083444</td>\n",
       "      <td>-0.022691</td>\n",
       "      <td>0.274366</td>\n",
       "      <td>0.297254</td>\n",
       "      <td>0.311005</td>\n",
       "      <td>0.288490</td>\n",
       "      <td>-0.112778</td>\n",
       "      <td>6179.400354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>411424</td>\n",
       "      <td>299.815747</td>\n",
       "      <td>14850.239602</td>\n",
       "      <td>13726.494448</td>\n",
       "      <td>292.481814</td>\n",
       "      <td>295.720253</td>\n",
       "      <td>297.378545</td>\n",
       "      <td>287.914742</td>\n",
       "      <td>289.201820</td>\n",
       "      <td>292.084176</td>\n",
       "      <td>...</td>\n",
       "      <td>0.473223</td>\n",
       "      <td>0.489423</td>\n",
       "      <td>-0.004536</td>\n",
       "      <td>0.177667</td>\n",
       "      <td>0.311335</td>\n",
       "      <td>0.336747</td>\n",
       "      <td>0.358535</td>\n",
       "      <td>0.324961</td>\n",
       "      <td>-0.095873</td>\n",
       "      <td>7380.460870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>411724</td>\n",
       "      <td>299.896044</td>\n",
       "      <td>14843.030831</td>\n",
       "      <td>13707.298647</td>\n",
       "      <td>291.285007</td>\n",
       "      <td>294.740088</td>\n",
       "      <td>296.714832</td>\n",
       "      <td>287.775871</td>\n",
       "      <td>288.748637</td>\n",
       "      <td>291.618313</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500529</td>\n",
       "      <td>0.466324</td>\n",
       "      <td>0.113345</td>\n",
       "      <td>0.154379</td>\n",
       "      <td>0.338580</td>\n",
       "      <td>0.332048</td>\n",
       "      <td>0.350418</td>\n",
       "      <td>0.305831</td>\n",
       "      <td>-0.111334</td>\n",
       "      <td>5993.838377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>411324</td>\n",
       "      <td>298.352775</td>\n",
       "      <td>14827.635700</td>\n",
       "      <td>13820.220001</td>\n",
       "      <td>291.082756</td>\n",
       "      <td>295.362329</td>\n",
       "      <td>296.653374</td>\n",
       "      <td>287.667187</td>\n",
       "      <td>288.716932</td>\n",
       "      <td>291.872847</td>\n",
       "      <td>...</td>\n",
       "      <td>0.477182</td>\n",
       "      <td>0.436834</td>\n",
       "      <td>0.015554</td>\n",
       "      <td>-0.104940</td>\n",
       "      <td>0.311719</td>\n",
       "      <td>0.321636</td>\n",
       "      <td>0.305963</td>\n",
       "      <td>0.288193</td>\n",
       "      <td>-0.115831</td>\n",
       "      <td>5321.619139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>410122</td>\n",
       "      <td>299.869901</td>\n",
       "      <td>14920.174305</td>\n",
       "      <td>13713.055760</td>\n",
       "      <td>293.225614</td>\n",
       "      <td>297.054824</td>\n",
       "      <td>297.727990</td>\n",
       "      <td>288.060986</td>\n",
       "      <td>289.553466</td>\n",
       "      <td>292.993147</td>\n",
       "      <td>...</td>\n",
       "      <td>0.398166</td>\n",
       "      <td>0.384400</td>\n",
       "      <td>-0.283487</td>\n",
       "      <td>-0.100682</td>\n",
       "      <td>0.231307</td>\n",
       "      <td>0.283026</td>\n",
       "      <td>0.317185</td>\n",
       "      <td>0.285569</td>\n",
       "      <td>-0.119494</td>\n",
       "      <td>5738.673461</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>510 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       NAME  AvgSurfT_inst_chengshu  LST_Day_1km_chousui   \n",
       "0    410522              300.526136         14799.390577  \\\n",
       "1    410421              299.835257         14885.097859   \n",
       "2    411726              297.580502         14859.105485   \n",
       "3    410822              301.204888         14937.506019   \n",
       "4    411082              301.276045         14916.375598   \n",
       "..      ...                     ...                  ...   \n",
       "505  411081              299.835151         14885.009553   \n",
       "506  411424              299.815747         14850.239602   \n",
       "507  411724              299.896044         14843.030831   \n",
       "508  411324              298.352775         14827.635700   \n",
       "509  410122              299.869901         14920.174305   \n",
       "\n",
       "     LST_Night_1km_fennie  soil_temperature_level_2_kaihua   \n",
       "0            13645.564675                       290.520730  \\\n",
       "1            13730.892892                       289.450286   \n",
       "2            13781.911220                       288.378218   \n",
       "3            13697.783412                       290.480633   \n",
       "4            13670.887570                       290.072776   \n",
       "..                    ...                              ...   \n",
       "505          13761.025977                       292.395091   \n",
       "506          13726.494448                       292.481814   \n",
       "507          13707.298647                       291.285007   \n",
       "508          13820.220001                       291.082756   \n",
       "509          13713.055760                       293.225614   \n",
       "\n",
       "     soil_temperature_level_2_guanjiang  soil_temperature_level_2_shouhuo   \n",
       "0                            296.243766                        301.744997  \\\n",
       "1                            295.121816                        301.575876   \n",
       "2                            293.032866                        298.607515   \n",
       "3                            296.267731                        302.175285   \n",
       "4                            295.931929                        302.736960   \n",
       "..                                  ...                               ...   \n",
       "505                          296.486793                        297.041116   \n",
       "506                          295.720253                        297.378545   \n",
       "507                          294.740088                        296.714832   \n",
       "508                          295.362329                        296.653374   \n",
       "509                          297.054824                        297.727990   \n",
       "\n",
       "     soil_temperature_level_3_chousui  soil_temperature_level_3_kaihua   \n",
       "0                          287.739688                       288.165064  \\\n",
       "1                          287.200556                       287.550367   \n",
       "2                          286.204292                       286.648051   \n",
       "3                          287.549117                       288.053063   \n",
       "4                          287.686706                       288.086720   \n",
       "..                                ...                              ...   \n",
       "505                        287.623432                       289.041457   \n",
       "506                        287.914742                       289.201820   \n",
       "507                        287.775871                       288.748637   \n",
       "508                        287.667187                       288.716932   \n",
       "509                        288.060986                       289.553466   \n",
       "\n",
       "     soil_temperature_level_3_guanjiang  ...  SVAI_yunsui  SVAI_kaihua   \n",
       "0                            291.989798  ...     0.516056     0.454165  \\\n",
       "1                            291.430691  ...     0.503922     0.415995   \n",
       "2                            290.173229  ...     0.457841     0.388374   \n",
       "3                            291.999239  ...     0.460758     0.391151   \n",
       "4                            292.011540  ...     0.498366     0.463834   \n",
       "..                                  ...  ...          ...          ...   \n",
       "505                          292.435764  ...     0.433611     0.419890   \n",
       "506                          292.084176  ...     0.473223     0.489423   \n",
       "507                          291.618313  ...     0.500529     0.466324   \n",
       "508                          291.872847  ...     0.477182     0.436834   \n",
       "509                          292.993147  ...     0.398166     0.384400   \n",
       "\n",
       "     WDRVI_bajie  WDRVI_chousui  WDVI_bajie  WDVI_yunsui  WDVI_chousui   \n",
       "0      -0.169349       0.059633    0.271899     0.369314      0.377903  \\\n",
       "1      -0.226778       0.047456    0.313414     0.345419      0.333503   \n",
       "2      -0.207561      -0.107692    0.246060     0.326980      0.303260   \n",
       "3      -0.225149       0.006908    0.295417     0.331463      0.379692   \n",
       "4      -0.114041       0.054913    0.330209     0.362398      0.363948   \n",
       "..           ...            ...         ...          ...           ...   \n",
       "505    -0.083444      -0.022691    0.274366     0.297254      0.311005   \n",
       "506    -0.004536       0.177667    0.311335     0.336747      0.358535   \n",
       "507     0.113345       0.154379    0.338580     0.332048      0.350418   \n",
       "508     0.015554      -0.104940    0.311719     0.321636      0.305963   \n",
       "509    -0.283487      -0.100682    0.231307     0.283026      0.317185   \n",
       "\n",
       "     WDVI_kaihua  wet_kaihua           亩产  \n",
       "0       0.332052   -0.085087  7421.059765  \n",
       "1       0.303379   -0.090472  5905.753158  \n",
       "2       0.274792   -0.110333  5681.763483  \n",
       "3       0.314127   -0.082004  7947.794351  \n",
       "4       0.328066   -0.095346  7840.499426  \n",
       "..           ...         ...          ...  \n",
       "505     0.288490   -0.112778  6179.400354  \n",
       "506     0.324961   -0.095873  7380.460870  \n",
       "507     0.305831   -0.111334  5993.838377  \n",
       "508     0.288193   -0.115831  5321.619139  \n",
       "509     0.285569   -0.119494  5738.673461  \n",
       "\n",
       "[510 rows x 61 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4a117973-8634-4679-8251-f818d42ab8c0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#d=d.drop(columns=['GNDVI_chousui','SR_yunsui','WDRVI_chousui','SVAI_chousui','SR_chousui'])\n",
    "#dd=dd.drop(columns=['GNDVI_chousui','SR_yunsui','WDRVI_chousui','SVAI_chousui','SR_chousui'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "299d2aaa-7024-4510-a82e-7a8c7e2bce87",
   "metadata": {
    "toc-hr-collapsed": true
   },
   "source": [
    "### 全部入模"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb44f0d2-fe74-49c3-9dae-5d02bfce9b25",
   "metadata": {},
   "source": [
    "### XGBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0abdea48-3748-4d1e-b08f-5665e2ef1557",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train =d.drop(columns = [\"亩产\"])\n",
    "y_train = d['亩产']\n",
    "x_test =dd.drop(columns = [\"亩产\"])\n",
    "y_test = dd['亩产']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1464b22a-0548-4270-8a61-ec3f0248a7ba",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "xgb_model = xgb.XGBRegressor(n_estimators=150,max_depth=5,learning_rate=0.1,random_state=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a97eacd2-35ef-4a3e-9d6d-18145e4d85ae",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "xgb_model_fit=xgb_model.fit(x_train, y_train)\n",
    "# 进行预测\n",
    "y_pred = xgb_model_fit.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e773e5d5-dc05-4490-8cf7-e4b09b6b7861",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>平均绝对误差（MAPE）</th>\n",
       "      <th>平均绝对误差（MAE）</th>\n",
       "      <th>均方根误差（RMSE）</th>\n",
       "      <th>决定系数（R^2）</th>\n",
       "      <th>解释方差</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>xgboost</th>\n",
       "      <td>0.064543</td>\n",
       "      <td>371.360375</td>\n",
       "      <td>516.974691</td>\n",
       "      <td>0.851664</td>\n",
       "      <td>0.852063</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         平均绝对误差（MAPE）  平均绝对误差（MAE）  均方根误差（RMSE）  决定系数（R^2）      解释方差\n",
       "xgboost      0.064543   371.360375   516.974691   0.851664  0.852063"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 平均绝对百分比误差\n",
    "mape=mean_absolute_percentage_error(y_test,y_pred)\n",
    "rmse = mean_squared_error(y_test, y_pred, squared=False)\n",
    "# 计算平均绝对误差（MAE）\n",
    "mae = mean_absolute_error(y_test, y_pred)\n",
    "# 计算决定系数（R^2）\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "# 计算解释方差分\n",
    "explained_var = explained_variance_score(y_test, y_pred)\n",
    "\n",
    "results2 = pd.DataFrame()\n",
    "results2['平均绝对误差（MAPE）'] = [mape]\n",
    "results2['平均绝对误差（MAE）'] = [mae]\n",
    "results2['均方根误差（RMSE）'] = [rmse]\n",
    "results2['决定系数（R^2）'] = [r2]\n",
    "results2['解释方差'] = [explained_var]\n",
    "results2.index = ['xgboost']\n",
    "results2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4d09d942-6273-4141-b32c-f4277825e744",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_test_sorted = np.sort(y_test)\n",
    "y_pred_sorted = y_pred[np.argsort(y_test)]\n",
    "\n",
    "# 绘制折线对比图\n",
    "plt.plot(range(len(y_test_sorted)), y_test_sorted, label='Actual')\n",
    "plt.plot(range(len(y_pred_sorted)), y_pred_sorted, label='Predicted',linestyle='--')\n",
    "#plt.xlabel('Index')\n",
    "plt.ylabel('Value')\n",
    "plt.title('Actual vs. Predicted (XGBoost)')\n",
    "plt.legend()\n",
    "plt.ylim(0, 10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1126e336-9818-460a-a45b-9d75e9cf4372",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.scatter(y_test, y_pred, alpha=0.5, label='Data Points')\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.title('XGBoost Scatter Plot of Actual vs. Predicted Values')\n",
    "\n",
    "# 添加对角线\n",
    "max_value = max(max(y_test), max(y_pred))\n",
    "min_value = min(min(y_test), min(y_pred))\n",
    "plt.plot([min_value, max_value], [min_value, max_value], color='red', linestyle='--', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e45f6acb-9b88-410a-8610-9e47b41cf47a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y_test</th>\n",
       "      <th>y_pred</th>\n",
       "      <th>precent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7467.000138</td>\n",
       "      <td>7031.933594</td>\n",
       "      <td>-5.83%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5972.666001</td>\n",
       "      <td>6393.281250</td>\n",
       "      <td>7.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5687.791498</td>\n",
       "      <td>5632.632324</td>\n",
       "      <td>-0.97%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7959.597222</td>\n",
       "      <td>7307.732422</td>\n",
       "      <td>-8.19%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7662.496889</td>\n",
       "      <td>7662.821289</td>\n",
       "      <td>0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>6613.422500</td>\n",
       "      <td>7483.548340</td>\n",
       "      <td>13.16%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>7579.469809</td>\n",
       "      <td>7479.232422</td>\n",
       "      <td>-1.32%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>5754.140236</td>\n",
       "      <td>6348.062012</td>\n",
       "      <td>10.32%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>5467.128359</td>\n",
       "      <td>6105.768066</td>\n",
       "      <td>11.68%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>6637.200003</td>\n",
       "      <td>6047.032715</td>\n",
       "      <td>-8.89%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>102 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          y_test       y_pred precent\n",
       "0    7467.000138  7031.933594  -5.83%\n",
       "1    5972.666001  6393.281250   7.04%\n",
       "2    5687.791498  5632.632324  -0.97%\n",
       "3    7959.597222  7307.732422  -8.19%\n",
       "4    7662.496889  7662.821289   0.00%\n",
       "..           ...          ...     ...\n",
       "97   6613.422500  7483.548340  13.16%\n",
       "98   7579.469809  7479.232422  -1.32%\n",
       "99   5754.140236  6348.062012  10.32%\n",
       "100  5467.128359  6105.768066  11.68%\n",
       "101  6637.200003  6047.032715  -8.89%\n",
       "\n",
       "[102 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test_array = np.array(y_test)\n",
    "\n",
    "y_pred_series = pd.Series(y_pred, name='y_pred')\n",
    "y_test_series = pd.Series(y_test_array, name='y_test')\n",
    "dftest1= pd.concat([y_test_series, y_pred_series], axis=1)\n",
    "dftest1['precent'] = ((dftest1['y_pred'] - dftest1['y_test']) / dftest1['y_test']) * 100\n",
    "dftest1['precent'] = dftest1['precent'].apply(lambda x: '{:.2f}%'.format(x))\n",
    "dftest1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4ac5507-b4b6-4b56-b7fc-5c755fc582e1",
   "metadata": {},
   "source": [
    "### RF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2ffd5e60-1017-44fd-89aa-b0a3f3605484",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train =d.drop(columns = [\"亩产\"])\n",
    "y_train = d['亩产']\n",
    "x_test =dd.drop(columns = [\"亩产\"])\n",
    "y_test = dd['亩产']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f2a1222e-86b4-4a69-bad2-c1ea1fa3da67",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "RF_model = RandomForestRegressor(n_estimators=150,max_depth=5,random_state=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f5fe7dcb-05b6-41f4-8e3d-1d5a4f367883",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "RF_model_fit=RF_model.fit(x_train, y_train)\n",
    "y_pred_rf = RF_model_fit.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bda5d553-3a1a-489a-a224-1a2513133ae0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>平均绝对误差（MAPE）</th>\n",
       "      <th>平均绝对误差（MAE）</th>\n",
       "      <th>均方根误差（RMSE）</th>\n",
       "      <th>决定系数（R^2）</th>\n",
       "      <th>解释方差</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RF</th>\n",
       "      <td>0.082616</td>\n",
       "      <td>483.891064</td>\n",
       "      <td>632.127801</td>\n",
       "      <td>0.778222</td>\n",
       "      <td>0.786257</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    平均绝对误差（MAPE）  平均绝对误差（MAE）  均方根误差（RMSE）  决定系数（R^2）      解释方差\n",
       "RF      0.082616   483.891064   632.127801   0.778222  0.786257"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# 平均绝对百分比误差\n",
    "mape=mean_absolute_percentage_error(y_test,y_pred_rf)\n",
    "rmse = mean_squared_error(y_test, y_pred_rf, squared=False)\n",
    "# 计算平均绝对误差（MAE）\n",
    "mae = mean_absolute_error(y_test, y_pred_rf)\n",
    "# 计算决定系数（R^2）\n",
    "r2 = r2_score(y_test, y_pred_rf)\n",
    "# 计算解释方差分\n",
    "explained_var = explained_variance_score(y_test, y_pred_rf)\n",
    "\n",
    "results3 = pd.DataFrame()\n",
    "results3['平均绝对误差（MAPE）'] = [mape]\n",
    "results3['平均绝对误差（MAE）'] = [mae]\n",
    "results3['均方根误差（RMSE）'] = [rmse]\n",
    "results3['决定系数（R^2）'] = [r2]\n",
    "results3['解释方差'] = [explained_var]\n",
    "results3.index = ['RF']\n",
    "results3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "73bff509-c7cd-4789-9be9-3db3ec683768",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_test_sorted = np.sort(y_test)\n",
    "y_pred_sorted = y_pred_rf[np.argsort(y_test)]\n",
    "\n",
    "# 绘制折线对比图\n",
    "plt.plot(range(len(y_test_sorted)), y_test_sorted, label='Actual')\n",
    "plt.plot(range(len(y_pred_sorted)), y_pred_sorted, label='Predicted',linestyle='--')\n",
    "#plt.xlabel('Index')\n",
    "plt.ylabel('Value')\n",
    "plt.title('Actual vs. Predicted (RF)')\n",
    "plt.legend()\n",
    "plt.ylim(0, 10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6ea5fc90-4bee-49db-9179-cfe6b2d27ea3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.scatter(y_test, y_pred_rf, alpha=0.5, label='Data Points')\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.title('RF Scatter Plot of Actual vs. Predicted Values')\n",
    "\n",
    "# 添加对角线\n",
    "max_value = max(max(y_test), max(y_pred))\n",
    "min_value = min(min(y_test), min(y_pred))\n",
    "plt.plot([min_value, max_value], [min_value, max_value], color='red', linestyle='--', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83f82718-8be0-4e17-9515-b3817d90d869",
   "metadata": {
    "tags": []
   },
   "source": [
    "### GBDT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8f0d03d9-087a-4261-b72e-e81981dbbbac",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train =d.drop(columns = [\"亩产\"])\n",
    "y_train = d['亩产']\n",
    "x_test =dd.drop(columns = [\"亩产\"])\n",
    "y_test = dd['亩产']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "dba56f2b-e52a-49af-8dab-062d9c88a18a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "gbdt_model = GradientBoostingRegressor(n_estimators=150,max_depth=5, learning_rate=0.1,random_state=100)\n",
    "gbdt_model_fit=gbdt_model.fit(x_train, y_train)\n",
    "# 进行预测\n",
    "y_pred_g = gbdt_model_fit.predict(x_test)# 使用训练数据拟合模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "836ccd88-bb65-4c30-9224-9492e15a1a87",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>平均绝对误差（MAPE）</th>\n",
       "      <th>平均绝对误差（MAE）</th>\n",
       "      <th>均方根误差（RMSE）</th>\n",
       "      <th>决定系数（R^2）</th>\n",
       "      <th>解释方差</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>gbdt</th>\n",
       "      <td>0.070684</td>\n",
       "      <td>409.541392</td>\n",
       "      <td>555.19385</td>\n",
       "      <td>0.828921</td>\n",
       "      <td>0.828924</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      平均绝对误差（MAPE）  平均绝对误差（MAE）  均方根误差（RMSE）  决定系数（R^2）      解释方差\n",
       "gbdt      0.070684   409.541392    555.19385   0.828921  0.828924"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 平均绝对百分比误差\n",
    "mape=mean_absolute_percentage_error(y_test,y_pred_g)\n",
    "rmse = mean_squared_error(y_test, y_pred_g, squared=False)\n",
    "# 计算平均绝对误差（MAE）\n",
    "mae = mean_absolute_error(y_test, y_pred_g)\n",
    "# 计算决定系数（R^2）\n",
    "r2 = r2_score(y_test, y_pred_g)\n",
    "# 计算解释方差分\n",
    "explained_var = explained_variance_score(y_test, y_pred_g)\n",
    "\n",
    "results4 = pd.DataFrame()\n",
    "results4['平均绝对误差（MAPE）'] = [mape]\n",
    "results4['平均绝对误差（MAE）'] = [mae]\n",
    "results4['均方根误差（RMSE）'] = [rmse]\n",
    "results4['决定系数（R^2）'] = [r2]\n",
    "results4['解释方差'] = [explained_var]\n",
    "results4.index = ['gbdt']\n",
    "results4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b8b72daa-cc66-4636-820e-f9717174d6b4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "y_test_sorted = np.sort(y_test)\n",
    "y_pred_sorted = y_pred_g[np.argsort(y_test)]\n",
    "\n",
    "# 绘制折线对比图\n",
    "plt.plot(range(len(y_test_sorted)), y_test_sorted, label='Actual')\n",
    "plt.plot(range(len(y_pred_sorted)), y_pred_sorted, label='Predicted',linestyle='--')\n",
    "#plt.xlabel('Index')\n",
    "plt.ylabel('Value')\n",
    "plt.title('Actual vs. Predicted (gbdt)')\n",
    "plt.legend()\n",
    "plt.ylim(0, 10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9d369ca1-a72c-4772-abc8-d204207808a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.scatter(y_test, y_pred_g, alpha=0.5, label='Data Points')\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.title('GBDT Scatter Plot of Actual vs. Predicted Values')\n",
    "\n",
    "# 添加对角线\n",
    "max_value = max(max(y_test), max(y_pred))\n",
    "min_value = min(min(y_test), min(y_pred))\n",
    "plt.plot([min_value, max_value], [min_value, max_value], color='red', linestyle='--', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "91b25179-2c30-4f29-a204-fc9fa8806eaa",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "c = pd.concat([results2,results3,results4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c04f33a1-eb35-40d3-acde-eb239bae6719",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>平均绝对误差（MAPE）</th>\n",
       "      <th>平均绝对误差（MAE）</th>\n",
       "      <th>均方根误差（RMSE）</th>\n",
       "      <th>决定系数（R^2）</th>\n",
       "      <th>解释方差</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>xgboost</th>\n",
       "      <td>0.064543</td>\n",
       "      <td>371.360375</td>\n",
       "      <td>516.974691</td>\n",
       "      <td>0.851664</td>\n",
       "      <td>0.852063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RF</th>\n",
       "      <td>0.082616</td>\n",
       "      <td>483.891064</td>\n",
       "      <td>632.127801</td>\n",
       "      <td>0.778222</td>\n",
       "      <td>0.786257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gbdt</th>\n",
       "      <td>0.070684</td>\n",
       "      <td>409.541392</td>\n",
       "      <td>555.193850</td>\n",
       "      <td>0.828921</td>\n",
       "      <td>0.828924</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         平均绝对误差（MAPE）  平均绝对误差（MAE）  均方根误差（RMSE）  决定系数（R^2）      解释方差\n",
       "xgboost      0.064543   371.360375   516.974691   0.851664  0.852063\n",
       "RF           0.082616   483.891064   632.127801   0.778222  0.786257\n",
       "gbdt         0.070684   409.541392   555.193850   0.828921  0.828924"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dbff1227-f778-4d25-afea-e0bf26070234",
   "metadata": {},
   "outputs": [],
   "source": [
    "booster = xgb_model_fit.get_booster()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "cb9a4fdf-64ec-45d6-ab1f-464ea80ca371",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "importance_dict = booster.get_fscore()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3d081b4a-5b8c-47a4-abab-28d12019b9ef",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "importance_df = pd.DataFrame(list(importance_dict.items()), columns=['Feature', 'Importance'])\n",
    "importance_df = importance_df.sort_values(by='Importance', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e4a02fd1-e262-4081-89a4-e1826ceeb786",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Feature</th>\n",
       "      <th>Importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NAME</td>\n",
       "      <td>565.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AvgSurfT_inst_chengshu</td>\n",
       "      <td>268.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LST_Day_1km_chousui</td>\n",
       "      <td>186.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LST_Night_1km_fennie</td>\n",
       "      <td>179.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>soil_temperature_level_2_kaihua</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>soil_temperature_level_2_shouhuo</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>wet_kaihua</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>SoilMoi0_10cm_inst_chousui</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>SR_kaihua</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>soil_temperature_level_3_kaihua</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>VDVI_shouhuo</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>soil_temperature_level_3_chousui</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SoilMoi0_10cm_inst_kaihua</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>soil_temperature_level_2_guanjiang</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>WDVI_chousui</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>SoilMoi10_40cm_inst_chousui</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SoilMoi0_10cm_inst_guanjiang</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Lai_500m_kaihua</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>GCVI_kaihua</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SoilMoi10_40cm_inst_kaihua</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>WDVI_bajie</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>SoilMoi10_40cm_inst_guanjiang</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>GCVI_yunsui</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>EVI2_kaihua</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>DVI_bajie</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Lai_500m_bajie</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>soil_temperature_level_3_guanjiang</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Lai_500m_chousui</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>DVI_kaihua</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>GCVI_bajie</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>NDVI_bajie</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>EVI_chousui</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>DVI_yunsui</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>WDVI_kaihua</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>MSR_chousui</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>soil_temperature_level_1_guanjiang</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>EVI_kaihua</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Lai_500m_yunsui</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>WDVI_yunsui</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>OSAVI_kaihua</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>MCARI_kaihua</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>EVI_bajie</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>EVI_yunsui</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>DVI_chousui</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>MSR_yunsui</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>MCARI_yunsui</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>NDVI_yunsui</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>OSAVI_yunsui</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>EVI2_chousui</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>MSR_bajie</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>MCARI_bajie</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>EVI2_yunsui</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>EVI2_bajie</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>GNDVI_bajie</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>MCARI_chousui</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>OSAVI_bajie</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>WDRVI_chousui</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>SVAI_kaihua</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>WDRVI_bajie</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Feature  Importance\n",
       "0                                 NAME       565.0\n",
       "1               AvgSurfT_inst_chengshu       268.0\n",
       "2                  LST_Day_1km_chousui       186.0\n",
       "3                 LST_Night_1km_fennie       179.0\n",
       "4      soil_temperature_level_2_kaihua       110.0\n",
       "6     soil_temperature_level_2_shouhuo        99.0\n",
       "58                          wet_kaihua        89.0\n",
       "11          SoilMoi0_10cm_inst_chousui        86.0\n",
       "19                           SR_kaihua        85.0\n",
       "8      soil_temperature_level_3_kaihua        85.0\n",
       "17                        VDVI_shouhuo        74.0\n",
       "7     soil_temperature_level_3_chousui        71.0\n",
       "12           SoilMoi0_10cm_inst_kaihua        67.0\n",
       "5   soil_temperature_level_2_guanjiang        67.0\n",
       "56                        WDVI_chousui        64.0\n",
       "14         SoilMoi10_40cm_inst_chousui        55.0\n",
       "13        SoilMoi0_10cm_inst_guanjiang        52.0\n",
       "38                     Lai_500m_kaihua        50.0\n",
       "33                         GCVI_kaihua        47.0\n",
       "15          SoilMoi10_40cm_inst_kaihua        42.0\n",
       "54                          WDVI_bajie        42.0\n",
       "16       SoilMoi10_40cm_inst_guanjiang        42.0\n",
       "32                         GCVI_yunsui        41.0\n",
       "30                         EVI2_kaihua        41.0\n",
       "20                           DVI_bajie        40.0\n",
       "35                      Lai_500m_bajie        40.0\n",
       "9   soil_temperature_level_3_guanjiang        40.0\n",
       "37                    Lai_500m_chousui        39.0\n",
       "23                          DVI_kaihua        38.0\n",
       "31                          GCVI_bajie        37.0\n",
       "46                          NDVI_bajie        36.0\n",
       "18                         EVI_chousui        36.0\n",
       "21                          DVI_yunsui        34.0\n",
       "57                         WDVI_kaihua        33.0\n",
       "45                         MSR_chousui        33.0\n",
       "10  soil_temperature_level_1_guanjiang        32.0\n",
       "26                          EVI_kaihua        31.0\n",
       "36                     Lai_500m_yunsui        29.0\n",
       "55                         WDVI_yunsui        28.0\n",
       "50                        OSAVI_kaihua        28.0\n",
       "42                        MCARI_kaihua        26.0\n",
       "24                           EVI_bajie        24.0\n",
       "25                          EVI_yunsui        23.0\n",
       "22                         DVI_chousui        23.0\n",
       "44                          MSR_yunsui        23.0\n",
       "40                        MCARI_yunsui        20.0\n",
       "47                         NDVI_yunsui        18.0\n",
       "49                        OSAVI_yunsui        16.0\n",
       "29                        EVI2_chousui        16.0\n",
       "43                           MSR_bajie        16.0\n",
       "39                         MCARI_bajie        15.0\n",
       "28                         EVI2_yunsui        14.0\n",
       "27                          EVI2_bajie        13.0\n",
       "34                         GNDVI_bajie        12.0\n",
       "41                       MCARI_chousui        11.0\n",
       "48                         OSAVI_bajie         8.0\n",
       "53                       WDRVI_chousui         7.0\n",
       "51                         SVAI_kaihua         1.0\n",
       "52                         WDRVI_bajie         1.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importance_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79bea973-f2c8-4b02-897a-386c97639526",
   "metadata": {},
   "source": [
    "### lasso"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "58ecb57c-83ee-45d7-b32c-0e0c52681f36",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "x_train =d.drop(columns = [\"亩产\"])\n",
    "y_train = d['亩产']\n",
    "x_test =dd.drop(columns = [\"亩产\"])\n",
    "y_test = dd['亩产']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "50db4630-9358-4b53-93b5-85fcb4d4c283",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#lasso_model = Lasso(alpha=0.001,random_state=100)\n",
    "lasso_model = Lasso(alpha=10,random_state=100)\n",
    "lasso_model_fit=lasso_model.fit(x_train, y_train)\n",
    "y_pred_lasso = lasso_model_fit.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "4564e538-f28b-43c4-afff-e805fe772f49",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>平均绝对误差（MAPE）</th>\n",
       "      <th>平均绝对误差（MAE）</th>\n",
       "      <th>均方根误差（RMSE）</th>\n",
       "      <th>决定系数（R^2）</th>\n",
       "      <th>解释方差</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lasso</th>\n",
       "      <td>0.132085</td>\n",
       "      <td>713.385473</td>\n",
       "      <td>914.693492</td>\n",
       "      <td>0.535635</td>\n",
       "      <td>0.579359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       平均绝对误差（MAPE）  平均绝对误差（MAE）  均方根误差（RMSE）  决定系数（R^2）      解释方差\n",
       "lasso      0.132085   713.385473   914.693492   0.535635  0.579359"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mape=mean_absolute_percentage_error(y_test,y_pred_lasso)\n",
    "rmse = mean_squared_error(y_test, y_pred_lasso, squared=False)\n",
    "# 计算平均绝对误差（MAE）\n",
    "mae = mean_absolute_error(y_test, y_pred_lasso)\n",
    "# 计算决定系数（R^2）\n",
    "r2 = r2_score(y_test, y_pred_lasso)\n",
    "# 计算解释方差分\n",
    "explained_var = explained_variance_score(y_test, y_pred_lasso)\n",
    "\n",
    "results5 = pd.DataFrame()\n",
    "results5['平均绝对误差（MAPE）'] = [mape]\n",
    "results5['平均绝对误差（MAE）'] = [mae]\n",
    "results5['均方根误差（RMSE）'] = [rmse]\n",
    "results5['决定系数（R^2）'] = [r2]\n",
    "results5['解释方差'] = [explained_var]\n",
    "results5.index = ['lasso']\n",
    "results5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "7d98f1fc-7b5c-4521-a14d-158eb74cb8b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.rcParams['font.size']=15 \n",
    "plt.scatter(y_test, y_pred, alpha=0.5, label='XGBoost')\n",
    "plt.scatter(y_test, y_pred_rf, alpha=0.5, label='RF',marker='^')\n",
    "plt.scatter(y_test, y_pred_g, alpha=0.5, label='GBDT',marker='*')\n",
    "plt.scatter(y_test, y_pred_lasso, alpha=0.5, label='lasso',marker='s')\n",
    "plt.xlabel('Actual Values',fontsize=20)\n",
    "plt.ylabel('Predicted Values',fontsize=20)\n",
    "#plt.title('Scatter Plot of Actual vs. Predicted Values')\n",
    "#plt.xlim(0, 1400)\n",
    "#plt.ylim(0, 1400)\n",
    "# 添加对角线\n",
    "max_value = max(max(y_test), max(y_pred))\n",
    "min_value = min(min(y_test), min(y_pred))\n",
    "plt.plot([min_value, max_value], [min_value, max_value], color='red', linestyle='--', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "63efb516-0cb6-4a4e-961b-8163addc9c46",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.rcParams['font.size'] = 15 \n",
    "\n",
    "# 绘制散点图并添加拟合线\n",
    "def plot_scatter_and_fit(x, y, label, marker='o'):\n",
    "    plt.scatter(x, y, alpha=0.5, label=label, marker=marker)\n",
    "    \n",
    "    # 计算线性拟合\n",
    "    z = np.polyfit(x, y, 1)\n",
    "    p = np.poly1d(z)\n",
    "    \n",
    "    # 绘制拟合线\n",
    "    x_fit = np.linspace(min(x), max(x), 100)\n",
    "    plt.plot(x_fit, p(x_fit), linestyle='--', label=f'{label} Fit')\n",
    "\n",
    "# 绘制每个模型的散点图和拟合线\n",
    "plot_scatter_and_fit(y_test, y_pred, 'XGBoost')\n",
    "plot_scatter_and_fit(y_test, y_pred_rf, 'RF', marker='^')\n",
    "plot_scatter_and_fit(y_test, y_pred_g, 'GBDT', marker='*')\n",
    "plot_scatter_and_fit(y_test, y_pred_lasso, 'lasso', marker='s')\n",
    "\n",
    "# 添加对角线\n",
    "max_value = max(max(y_test), max(y_pred))\n",
    "min_value = min(min(y_test), min(y_pred))\n",
    "plt.plot([min_value, max_value], [min_value, max_value], color='black', linestyle='-', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "plt.xlabel('Actual Values', fontsize=20)\n",
    "plt.ylabel('Predicted Values', fontsize=20)\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5a97c24e-d183-44b6-aab1-e3b24caf83d7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "d.to_excel('数据\\入模特征.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "fe4667b5-d69a-4b73-b09a-18e602be82b9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "dd.to_excel('数据\\入模特征1.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db22f5db-d88d-4cd8-85f5-4b70d8122db3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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